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BACKGROUND: A poor diet can result from adverse social determinants of health and increases the risk of adverse pregnancy outcomes. OBJECTIVE: We aimed to assess, using data from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be prospective cohort, whether nulliparous pregnant individuals who lived in a food desert were more likely to experience poorer periconceptional diet quality compared with those who did not live in a food desert. METHODS: The exposure was living in a food desert based on a spatial overview of food access indicators by income and supermarket access per the Food Access Research Atlas. The outcome was periconceptional diet quality per the Healthy Eating Index (HEI)-2010, analyzed by quartile (Q) from the highest or best (Q4, reference) to the lowest or worst dietary quality (Q1); and secondarily, nonadherence (yes or no) to 12 key aspects of dietary quality. RESULTS: Among 7,956 assessed individuals, 24.9% lived in a food desert. The mean HEI-2010 score was 61.1 of 100 (SD: 12.5). Poorer periconceptional dietary quality was more common among those who lived in a food desert compared with those who did not live in a food desert (Q4: 19.8%, Q3: 23.6%, Q2: 26.5%, and Q1: 30.0% vs. Q4: 26.8%, Q3: 25.8%, Q2: 24.5%, and Q1: 22.9%; overall P < 0.001). Individuals living in a food desert were more likely to report a diet in lower quartiles of the HEI-2010 (i.e., poorer dietary quality) (aOR: 1.34 per quartile; 95% CI: 1.21, 1.49). They were more likely to be nonadherent to recommended standards for 5 adequacy components of the HEI-2010, including fruit, total vegetables, greens and beans, seafood and plant proteins, and fatty acids, and less likely to report excess intake of empty calories. CONCLUSIONS: Nulliparous pregnant individuals living in a food desert were more likely to experience poorer periconceptional diet quality compared with those who did not live in a food desert.
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Dieta , Desertos Alimentares , Gravidez , Feminino , Humanos , Estudos Prospectivos , Resultado da Gravidez , VerdurasRESUMO
This article introduces the R (R Core Team 2019) package BayesCTDesign for two-arm randomized Bayesian trial design using historical control data when available, and simple two-arm randomized Bayesian trial design when historical control data is not available. The package BayesCTDesign, which is available on CRAN, has two simulation functions, historic_sim() and simple_sim() for studying trial characteristics under user defined scenarios, and two methods print() and plot() for displaying summaries of the simulated trial characteristics. The package BayesCTDesign works with two-arm trials with equal sample sizes per arm. The package BayesCTDesign allows a user to study Gaussian, Poisson, Bernoulli, Weibull, Lognormal, and Piecewise Exponential (pwe) outcomes. Power for two-sided hypothesis tests at a user defined alpha is estimated via simulation using a test within each simulation replication that involves comparing a 95% credible interval for the outcome specific treatment effect measure to the null case value. If the 95% credible interval excludes the null case value, then the null hypothesis is rejected, else the null hypothesis is accepted. In the article, the idea of including historical control data in a Bayesian analysis is reviewed, the estimation process of BayesCTDesign is explained, and the user interface is described. Finally, the BayesCTDesign is illustrated via several examples.
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BACKGROUND: Individual adverse social determinants of health are associated with increased risk of diabetes in pregnancy, but the relative influence of neighborhood or community-level social determinants of health is unknown. OBJECTIVE: This study aimed to determine whether living in neighborhoods with greater socioeconomic disadvantage, food deserts, or less walkability was associated with having pregestational diabetes and developing gestational diabetes. STUDY DESIGN: We conducted a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. Home addresses in the first trimester were geocoded at the census tract level. The exposures (modeled separately) were the following 3 neighborhood-level measures of adverse social determinants of health: (1) socioeconomic disadvantage, defined by the Area Deprivation Index and measured in tertiles from the lowest tertile (ie, least disadvantage [T1]) to the highest (ie, most disadvantage [T3]); (2) food desert, defined by the United States Department of Agriculture Food Access Research Atlas (yes/no by low income and low access criteria); and (3) less walkability, defined by the Environmental Protection Agency National Walkability Index (most walkable score [15.26-20.0] vs less walkable score [<15.26]). Multinomial logistic regression was used to model the odds of gestational diabetes or pregestational diabetes relative to no diabetes as the reference, adjusted for age at delivery, chronic hypertension, Medicaid insurance status, and low household income (<130% of the US poverty level). RESULTS: Among the 9155 assessed individuals, the mean Area Deprivation Index score was 39.0 (interquartile range, 19.0-71.0), 37.0% lived in a food desert, and 41.0% lived in a less walkable neighborhood. The frequency of pregestational and gestational diabetes diagnosis was 1.5% and 4.2%, respectively. Individuals living in a community in the highest tertile of socioeconomic disadvantage had increased odds of entering pregnancy with pregestational diabetes compared with those in the lowest tertile (T3 vs T1: 2.6% vs 0.8%; adjusted odds ratio, 2.52; 95% confidence interval, 1.41-4.48). Individuals living in a food desert (4.8% vs 4.0%; adjusted odds ratio, 1.37; 95% confidence interval, 1.06-1.77) and in a less walkable neighborhood (4.4% vs 3.8%; adjusted odds ratio, 1.33; 95% confidence interval, 1.04-1.71) had increased odds of gestational diabetes. There was no significant association between living in a food desert or a less walkable neighborhood and pregestational diabetes, or between socioeconomic disadvantage and gestational diabetes. CONCLUSION: Nulliparous individuals living in a neighborhood with higher socioeconomic disadvantage were at increased odds of entering pregnancy with pregestational diabetes, and those living in a food desert or a less walkable neighborhood were at increased odds of developing gestational diabetes, after controlling for known covariates.
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Diabetes Gestacional , Gravidez , Feminino , Estados Unidos/epidemiologia , Humanos , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/epidemiologia , Determinantes Sociais da Saúde , Estudos Prospectivos , Características de Residência , Resultado da GravidezRESUMO
OBJECTIVE: To examine whether exposure to community or neighborhood socioeconomic disadvantage as measured by the ADI (Area Deprivation Index) is associated with risk of abnormal birth weight among nulliparous individuals with singleton gestations. METHODS: This was a secondary analysis from the prospective cohort NuMoM2b study (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be). Participant addresses at cohort enrollment between 6 and 13 weeks of gestation were geocoded at the Census tract level and linked to the 2015 ADI. The ADI, which incorporates the domains of income, education, employment, and housing quality into a composite national ranking of neighborhood socioeconomic disadvantage, was categorized by quartiles (quartile 1, least disadvantaged, reference; quartile 4, most disadvantaged). Outcomes were large for gestational age (LGA; birth weight at or above the 90th percentile) and small for gestational age (SGA; birth weight below the 10th percentile) compared with appropriate for gestational age (AGA; birth weight 10th-90th percentile) as determined with the 2017 U.S. natality reference data, standardized for fetal sex. Multinomial logistic regression models were adjusted for potential confounding variables. RESULTS: Of 8,983 assessed deliveries in the analytic population, 12.7% (n=1,143) were SGA, 8.2% (n=738) were LGA, and 79.1% (n=7,102) were AGA. Pregnant individuals living in the highest ADI quartile (quartile 4, 17.8%) had an increased odds of delivering an SGA neonate compared with those in the lowest referent quartile (quartile 1, 12.4%) (adjusted odds ratio [aOR] 1.32, 95% CI 1.09-1.55). Pregnant individuals living in higher ADI quartiles (quartile 2, 10.3%; quartile 3, 10.7%; quartile 4, 9.2%) had an increased odds of delivering an LGA neonate compared with those in the lowest referent quartile (quartile 1, 8.2%) (aOR: quartile 2, 1.40, 95% CI 1.19-1.61; quartile 3, 1.35, 95% CI 1.09-1.61; quartile 4, 1.47, 95% CI 1.20-1.74). CONCLUSION: Neonates of nulliparous pregnant individuals living in U.S. neighborhoods with higher area deprivation were more likely to have abnormal birth weights at both extremes.
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Recém-Nascido Pequeno para a Idade Gestacional , Disparidades Socioeconômicas em Saúde , Recém-Nascido , Gravidez , Feminino , Humanos , Peso ao Nascer , Estudos Prospectivos , Retardo do Crescimento FetalRESUMO
We assessed whether neighborhood socioeconomic disadvantage, as measured by the Area Deprivation Index (ADI), was associated with an increased risk of postpartum readmission. This is a secondary analysis from nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be), a prospective cohort of nulliparous pregnant individuals from 2010 to 2013. The exposure was the ADI in quartiles, and the outcome was postpartum readmission; Poisson regression was used. Among 9,061 assessed individuals, 154 (1.7%) were readmitted postpartum within 2 weeks of delivery. Individuals living with the most neighborhood deprivation (ADI quartile 4) were at increased risk of postpartum readmission compared with those living with the lowest neighborhood deprivation (ADI quartile 1) (adjusted risk ratio 1.80, 95% CI 1.11-2.93). Measures of community-level adverse social determinants of health, such as the ADI, may inform postpartum care after delivery discharge.